| --- |
| license: other |
| license_name: research-only-mixed-upstream |
| license_link: https://github.com/zzh237/AgentBake |
| pretty_name: AgentBake Trace Library (100 heterogeneous agents, 7 frameworks) |
| size_categories: |
| - 1K<n<10K |
| tags: |
| - agents |
| - personalization |
| - benchmark |
| - multi-agent |
| - traces |
| --- |
| |
| # AgentBake Trace Library |
|
|
| Execution-trace corpus for the **AgentBake benchmark** (*A Personalization Layer |
| and Benchmark for Heterogeneous Agents*). 100 heterogeneous agents spanning |
| seven frameworks (AutoGen, CrewAI, LangChain, LangGraph, LlamaIndex, |
| PydanticAI, Strands), each contributing ~10 recorded multi-turn scenarios. |
|
|
| ## Contents |
|
|
| ``` |
| good_by_framework/ |
| autogen/<agent>/scenario_XXX/ |
| *__trace_sequence.json # per-step activations: input text, output, tools, timing |
| *__topology.json # agent graph: nodes, roles, declared capabilities |
| *__prebuilt_eval.json # LLM-judge scores (coherence, goal success, ...) |
| selection_metadata.json |
| crewai/ ... langchain/ ... langgraph/ ... llamaindex/ ... pydanticai/ ... strands/ |
| ``` |
|
|
| ~4,900 files, ~6.2 GB. 16/14/15/30/5/10/10 agents per framework. |
|
|
| ## Provenance |
|
|
| Traces were generated by executing rebuilt open-source agents (149-agent |
| adapter library, pinned upstream repos + commit SHAs in the companion code |
| repo) on synthetic task scenarios, with **Qwen3-32B** (`qwen.qwen3-32b-v1:0`, |
| via Amazon Bedrock) as the agent backend LLM and as the prebuilt evaluator |
| judge. The trace content (inputs, outputs, topologies, judge scores) is |
| generated data; upstream agent *code* is not included here — see the code |
| repository for the adapter library and per-repo licenses. |
|
|
| ## Usage |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| snapshot_download("zzh237/agentbake-traces", repo_type="dataset", |
| local_dir="data/multiagent_traces") |
| ``` |
|
|
| Then run the AgentBake benchmark from the code repo: |
| https://github.com/zzh237/AgentBake |
|
|
| ## Intended use |
|
|
| Research on agent personalization, orchestration-policy learning, and |
| benchmark evaluation. Scenarios are synthetic; no real user data. |
|
|
